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314 lines
8.6 KiB
C++
314 lines
8.6 KiB
C++
// This file is part of OpenCV project.
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// It is subject to the license terms in the LICENSE file found in the top-level directory
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// of this distribution and at http://opencv.org/license.html.
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/*
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StackBlur - a fast almost Gaussian Blur
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Theory: http://underdestruction.com/2004/02/25/stackblur-2004
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The code has been borrowed from (https://github.com/flozz/StackBlur).
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Below is the original copyright
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*/
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/*
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Copyright (c) 2010 Mario Klingemann
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Permission is hereby granted, free of charge, to any person
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obtaining a copy of this software and associated documentation
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files (the "Software"), to deal in the Software without
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restriction, including without limitation the rights to use,
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copy, modify, merge, publish, distribute, sublicense, and/or sell
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copies of the Software, and to permit persons to whom the
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Software is furnished to do so, subject to the following
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conditions:
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The above copyright notice and this permission notice shall be
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included in all copies or substantial portions of the Software.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
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EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
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OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
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NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
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HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
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WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
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FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
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OTHER DEALINGS IN THE SOFTWARE.
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*/
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#include "test_precomp.hpp"
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namespace opencv_test { namespace {
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template<typename T>
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void _stackblurRef(const Mat& src, Mat& dst, Size ksize)
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{
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CV_Assert(!src.empty());
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CV_Assert(ksize.width > 0 && ksize.height > 0 && ksize.height % 2 == 1 && ksize.width % 2 == 1);
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dst.create(src.size(), src.type());
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const int CN = src.channels();
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int rowsImg = src.rows;
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int colsImg = src.cols;
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int wm = colsImg - 1;
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int radiusW = ksize.width / 2;
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int stackLenW = ksize.width;
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const float mulW = 1.0f / (((float )radiusW + 1.0f) * ((float )radiusW + 1.0f));
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// Horizontal direction
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std::vector<T> stack(stackLenW * CN);
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for (int row = 0; row < rowsImg; row++)
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{
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std::vector<float> sum(CN, 0);
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std::vector<float> sumIn(CN, 0);
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std::vector<float> sumOut(CN, 0);
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const T* srcPtr = src.ptr<T>(row);
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for (int i = 0; i <= radiusW; i++)
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{
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for (int ci = 0; ci < CN; ci++)
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{
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T tmp = *(srcPtr + ci);
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stack[i * CN + ci] = tmp;
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sum[ci] += tmp * (i + 1);
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sumOut[ci] += tmp;
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}
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}
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for (int i = 1; i <= radiusW; i++)
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{
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if (i <= wm) srcPtr += CN;
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for(int ci = 0; ci < CN; ci++)
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{
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T tmp = *(srcPtr + ci);
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stack[(i + radiusW) * CN + ci] = tmp;
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sum[ci] += tmp * (radiusW + 1 - i);
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sumIn[ci] += tmp;
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}
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}
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int sp = radiusW;
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int xp = radiusW ;
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if (xp > wm) xp = wm;
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T* dstPtr = dst.ptr<T>(row);
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srcPtr = src.ptr<T>(row) + xp * CN;
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int stackStart= 0;
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for (int i = 0; i < colsImg; i++)
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{
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stackStart = sp + stackLenW - radiusW;
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if (stackStart >= stackLenW) stackStart -= stackLenW;
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for(int ci = 0; ci < CN; ci++)
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{
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*(dstPtr + ci) = cv::saturate_cast<T>(sum[ci] * mulW);
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sum[ci] -= sumOut[ci];
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sumOut[ci] -= stack[stackStart*CN + ci];
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}
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const T* srcNew = srcPtr;
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if(xp < wm)
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srcNew += CN;
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for (int ci = 0; ci < CN; ci++)
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{
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stack[stackStart * CN + ci] = *(srcNew + ci);
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sumIn[ci] += *(srcNew + ci);
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sum[ci] += sumIn[ci];
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}
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int sp1 = sp + 1;
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sp1 &= -(sp1 < stackLenW);
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for(int ci = 0; ci < CN; ci++)
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{
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T tmp = stack[sp1*CN + ci];
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sumOut[ci] += tmp;
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sumIn[ci] -= tmp;
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}
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dstPtr += CN;
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if (xp < wm)
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{
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xp++;
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srcPtr += CN;
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}
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++sp;
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if (sp >= stackLenW) sp = 0;
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}
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}
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// Vertical direction
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int hm = rowsImg - 1;
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int widthElem = colsImg * CN;
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int radiusH = ksize.height / 2;
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int stackLenH = ksize.height;
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const float mulH = 1.0f / (((float )radiusH + 1.0f) * ((float )radiusH + 1.0f));
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stack.resize(stackLenH, 0);
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for (int col = 0; col < widthElem; col++)
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{
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const T* srcPtr =dst.ptr<T>() + col;
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float sum0 = 0;
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float sumIn0 = 0;
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float sumOut0 = 0;
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for (int i = 0; i <= radiusH; i++)
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{
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T tmp = (T)(*srcPtr);
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stack[i] = tmp;
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sum0 += tmp * (i + 1);
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sumOut0 += tmp;
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}
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for (int i = 1; i <= radiusH; i++)
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{
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if (i <= hm) srcPtr += widthElem;
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T tmp = (T)(*srcPtr);
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stack[i + radiusH] = tmp;
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sum0 += tmp * (radiusH - i + 1);
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sumIn0 += tmp;
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}
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int sp = radiusH;
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int yp = radiusH;
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if (yp > hm) yp = hm;
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T* dstPtr = dst.ptr<T>() + col;
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srcPtr = dst.ptr<T>(yp) + col;
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const T* srcNew;
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int stackStart = 0;
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for (int i = 0; i < rowsImg; i++)
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{
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stackStart = sp + stackLenH - radiusH;
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if (stackStart >= stackLenH) stackStart -= stackLenH;
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*(dstPtr) = saturate_cast<T>(sum0 * mulH);
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sum0 -= sumOut0;
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sumOut0 -= stack[stackStart];
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srcNew = srcPtr;
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if (yp < hm)
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srcNew += widthElem;
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stack[stackStart] = *(srcNew);
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sumIn0 += *(srcNew);
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sum0 += sumIn0;
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int sp1 = sp + 1;
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sp1 &= -(sp1 < stackLenH);
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sumOut0 += stack[sp1];
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sumIn0 -= stack[sp1];
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dstPtr += widthElem;
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if (yp < hm)
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{
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yp++;
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srcPtr += widthElem;
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}
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++sp;
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if (sp >= stackLenH) sp = 0;
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}
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}
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}
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void stackBlurRef(const Mat& img, Mat& dst, Size ksize)
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{
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if(img.depth() == CV_8U)
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_stackblurRef<uchar>(img, dst, ksize);
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else if (img.depth() == CV_16S)
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_stackblurRef<short>(img, dst, ksize);
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else if (img.depth() == CV_16U)
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_stackblurRef<ushort>(img, dst, ksize);
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else if (img.depth() == CV_32F)
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_stackblurRef<float>(img, dst, ksize);
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else
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CV_Error_( CV_StsNotImplemented,
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("Unsupported Mat type in stackBlurRef, "
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"the supported formats are: CV_8U, CV_16U, CV_16S and CV_32F."));
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}
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std::vector<Size> kernelSizeVec = {
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Size(3, 3),
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Size(5, 5),
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Size(101, 101),
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Size(3, 9)
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};
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typedef testing::TestWithParam<tuple<int, int, int> > StackBlur;
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TEST_P (StackBlur, regression)
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{
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Mat img_ = imread(findDataFile("shared/fruits.png"), 1);
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const int cn = get<0>(GetParam());
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const int kIndex = get<1>(GetParam());
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const int dtype = get<2>(GetParam());
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Size ksize = kernelSizeVec[kIndex];
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Mat img, dstRef, dst;
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convert(img_, img, dtype);
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vector<Mat> channels;
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split(img, channels);
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channels.push_back(channels[0]); // channels size is 4.
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Mat imgCn;
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if (cn == 1)
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imgCn = channels[0];
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else if (cn == 4)
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merge(channels, imgCn);
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else
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imgCn = img;
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stackBlurRef(imgCn, dstRef, ksize);
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stackBlur(imgCn, dst, ksize);
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EXPECT_LE(cvtest::norm(dstRef, dst, NORM_INF), 2.);
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}
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INSTANTIATE_TEST_CASE_P(Imgproc, StackBlur,
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testing::Combine(
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testing::Values(1, 3, 4),
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testing::Values(0, 1, 2, 3),
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testing::Values(CV_8U, CV_16S, CV_16U, CV_32F)
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)
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);
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typedef testing::TestWithParam<tuple<int> > StackBlur_GaussianBlur;
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// StackBlur should produce similar results as GaussianBlur output.
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TEST_P(StackBlur_GaussianBlur, compare)
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{
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Mat img_ = imread(findDataFile("shared/fruits.png"), 1);
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const int dtype = get<0>(GetParam());
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Size ksize(3, 3);
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Mat img, dstS, dstG;
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convert(img_, img, dtype);
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stackBlur(img, dstS, ksize);
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GaussianBlur(img, dstG, ksize, 0);
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EXPECT_LE(cvtest::norm(dstS, dstG, NORM_INF), 13.);
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}
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INSTANTIATE_TEST_CASE_P(Imgproc, StackBlur_GaussianBlur, testing::Values(CV_8U, CV_16S, CV_16U, CV_32F));
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}
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}
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